Method for inspecting a reticle

ABSTRACT

Disclosed is a method of inspecting a reticle for defects that occur over time. The invention accomplishes this by generating and storing a “baseline” image of the reticle and then periodically generating a “current” image of the reticle and comparing the current and baseline images. The baseline image is taken at a time when the reticle is known to be acceptable. This may be when the reticle has been “qualified” by an optical test or when a die fabricated by reticle has passed an electrical test. Also disclosed in a method for compacting the baseline image before storage.

BACKGROUND OF THE INVENTION

The present invention relates to systems for determining whether areticle is defective. More particularly, the present invention relatesto systems and methods which identify reticle defects that arise at sometime after a reticle is “qualified” as being suitable for use.

A normal reticle or photomask is an optical element containingtransparent and opaque regions which together define the pattern ofcoplanar features in an electronic device such as an integrated circuit.A phase shift reticle, which is also well known in the art, may furtherinclude graded regions (with varying thickness) that cause a phase shiftof the transmitted light. In order to learn more about phase shiftreticles, reference may be made to book authored by Van Zant, Peter,entitled “Microchip Fabrication” McGraw-Hill, 1997, which isincorporated herein by reference for all purposes. Reticles are usedduring photolithography to define masks which protect specified regionsof a semiconductor wafer from etching, ion implantation, or otherfabrication process. For many modern integrated circuit designs, areticle's features are between about 4 and about 20 times larger thanthe corresponding feature size of the mask on the wafer.

Reticles are typically made from a transparent medium such as aborosilicate glass or quartz plate on which is deposited an opaquepattern of chromium or other suitable material. The reticle pattern maybe created by a laser or an e-beam direct write technique, for example,both of which are widely used in the art. The reticle is framed andcovered by a pellicle which is a thin layer of an optically neutralmaterial such as a polymer attached to the frame. Typically, an adhesiveis used to affix the pellicle to the frame. Once in place, the pellicle(positioned about 6 mm from the reticle) protects the reticle from dirtor dust particles in the environment. Such particles may deposit on thepellicle but do not affect the reticle's image because the pellicle islocated beyond the focal plane of the reticle.

During the normal course of the reticle's life, however, defects can beintroduced into the reticle. For example, particles may be present buthidden (on the chromium region for example) when the reticle isinitially formed. Over the course of time, some of these particles maymigrate onto the transparent regions where they degrade the imagequality. In another example, defects may be introduced into the reticleby “flaking” of the frame or the adhesive material that affixes thepellicle to the frame.

In yet another example, an electrostatic discharge (ESD) generated by astepper apparatus employed during conventional photolithography maydamage the opaque regions of the reticle.

If a reticle becomes defective due to one of the above mechanisms, forexample, it may have a very negative impact on the yield of an ICfabrication facility. For example, a particle spanning two opaque lineson a reticle may result in shorting between adjacent metal orpolysilicon lines. Other reticle defects may cause more subtle defectsthat can not easily be detected and may not be manifested until the ICsare in the customers' hands. Undetected, such defects can cost afacility many millions of dollars and potential embarrassment. Thus,many IC manufactures periodically image or otherwise test their reticlesto ensure that they are not defective.

FIG. 1A is an idealized representation of an actual “darkfield” image 10of a reticle obtained by scanning a light beam onto the reticle andmonitoring light scattered therefrom. In the actual image, variousregions of the image have varying shades of gray. In FIG. 1A, thevarious shades of gray could not be accurately depicted, so the contrastbetween features is exaggerated in some cases and reduced in othercases.

Image 10 of the reticle has a dark area 14, a bright area 16, and a verydark area 12. Areas 14 and 16 have certain relatively bright repetitivefeatures created by light scattering off of valid repetitive features onthe reticle surface. For example, dark area 14 includes vertical lines22 created by some repetitive feature on the reticle. Such imagepatterns created by valid structures may fool a detector into believingthat they constitute defects. Therefore these features are sometimesreferred to herein as “false defects.” In addition to vertical lines 22,dark area 14 also has a random bright spot 18 indicative of a reticledefect (hereinafter referred to as a “real defect”), which may be causedby an electrostatic discharge (ESD) for example.

Bright area 16 receives its brightness from bright bands 20 which arelight scattered off of valid die features (more examples “falsedefects”). Very dark area 12 contains very little scattered light and nobright spots that would represent real or false defects on the reticle.

As should be apparent from a study of FIG. 1A, various real and falsedefects may appear in an image. Obviously, a test system must be able toseparate the real from the false. Traditionally, this has beenaccomplished by employing a “die-to-die” comparison which may be carriedout in KLA 301 or 351 Reticle Inspection Tool, commercially availablefrom KLA-Tencor of San Jose, Calif.

In systems employing the die-to-die approach, the images of twosupposedly identical patterns on a reticle are compared. Note that manyreticles contain the patterns of multiple identical die, collectivelyreferred to as a field. Images of two or more of these individual diepatterns in a field are compared by optically overlaying the patterns.Such comparisons will screen the false defects because they will befound on the images of both die. Real defects presumably occur randomlyand therefore appear only on a single die. Thus, a comparison of two diepattern images will normally find a real defect on only a single diepattern. Thus, the imaging system will flag bright spots appearing ononly a single image as real defects.

FIG. 1B shows some significant components of a scattering or “darkfield”detecting assembly 50 that may be employed to scan a reticle surface andgenerate an image of the reticle or die pattern. An incident beam 56generated by an illuminating source 52, e.g., a laser, is directed at aportion of a reticle surface 54. Incident beam 56 travels along anincident axis 70 and perpendicular to an axis 72. First and seconddetectors 64 and 68, positioned at an oblique angle, e.g., 45°, withrespect to the incident axis 70, detect a first and second scatteredenergy signals 58 and 60, respectively, from reticle portion 54 afterthe scattered energy signals pass through filters 62 and 66.

During a typical inspection process of reticle portion 54, illuminatingsource 52 directs incident beam 56 to strike reticle portion 54 and aresulting scattered light signal is detected by first and seconddetectors 64 and 68. A defect residing at reticle portion 54 may,therefore, be flagged, if the intensity of the detected light signal isequal to or exceeds a predetermined threshold signal intensity. If,however, the intensity of the scattered energy signal detected is lessthan a predetermined threshold signal intensity, then reticle portion 54is considered to be free of defects. Typically, the source and detectorsare moved in a rasterized fashion to generate an image of the entirereticle.

During a die-to-die comparison in the same reticle, it may be difficultto discriminate between false defects and true defects. This is becausethere may be subtle differences between the dies that are notnecessarily true printable defects. For example, small differences infeature width may fall within acceptable tolerances but still show up asdefects on die-to-die comparisons. Further, some reticles contain apattern for a single die only. Obviously, in such cases die-to-diereticle inspection can not be implemented.

What is needed is an improved inspection system that rapidly andinexpensively determines whether a defect has appeared in a reticle.

SUMMARY OF THE INVENTION

The present invention provides a method of inspecting a reticle fordefects that occur over time. The invention accomplishes this bygenerating and storing a “baseline” image of the reticle and thenperiodically generating a “current” image of the reticle and comparingthe current and baseline images. The baseline image is taken at a timewhen the reticle is known to be acceptable. Often this is when thereticle has been “qualified” by an optical test or a die fabricated byreticle has been electrically tested. Because the comparison relies uponimages of the exact same portions of the reticle, the problems inherentin die-to-die techniques are avoided.

In some cases, the methods of this invention may be characterized by thefollowing sequence: (a) providing a baseline image of the reticle whichwas created while the reticle was qualified as being of acceptablequality; (b) generating a current image of the reticle (preferably inthe same manner as the baseline image); and (c) comparing the baselineand current images to identify any new defects that may have arisen inthe time between when the baseline image was created and when thecurrent image is generated.

The baseline and current images may be obtained by scanning the surfaceof the reticle with light from an illumination source. For each regionconsidered in the scan, the method may involve (i) illuminating a regionof the reticle by an incident beam generated by an illuminating source;(ii) detecting a scattered energy distribution from the region of thereticle by a detector; and (iii) recording the scattered energydistribution from the region of the reticle.

The baseline and current images may be compared by a process involvingfirst determining whether intensity of scattered radiation at a firstlocation of the current image is greater than a defined threshold; andif so, then determining whether a corresponding region of the baselineimage also contains scattered radiation of substantially the sameintensity. The initial comparison of the current image with a thresholdspeeds the overall comparison. If a particular portion of the currentimage does not exceed the threshold, then no significant scatteringoccurred there which means that the no defect resides there—regardlessof any comparison to the baseline image. If a direct comparison of thebaseline and current images is necessary, then those regions where theintensity value of the current image significantly exceeds thecorresponding intensity value of the baseline image are deemed tocontain a defect.

Various techniques may be employed to facilitate the general methods ofthis invention. For example, the baseline image may be compacted toreduce the quantity of stored data for portions of the image where theintensity of the scattered radiation does not exceed a definedthreshold. In a preferred embodiment, compacting includes the following:(i) segmenting the baseline image into regions of the reticle; and (ii)removing data from the baseline image for those regions of the reticlewhere the intensity of the scattered radiation does not exceed thedefined threshold.

In addition, multiple imaging algorithms may be employed to imagevarious regions of the reticle under evaluation. For each region, a bestalgorithm is selected. This best algorithm is better able todiscriminate between real and false defects than any other algorithms.In one embodiment, a suitable method includes the following sequence:(a) providing the reticle to be inspected; (b) generating dataspecifying intensity of radiation scattered from the reticle as afunction of location on the reticle; (c) defining a first portion of thedata which was derived from a first region on the reticle; (d) applyinga plurality of imaging algorithms to the first portion of the data; (e)selecting a first imaging algorithm from among the plurality of imagingalgorithms based upon ability to suppress scattered radiation from validfeatures on first region of the reticle; and (f) associating the firstimaging algorithm with the first portion of data in the baseline image,such that during the subsequent inspections of the reticle the firstimaging algorithm is applied to the first portion of the data to providean image of the first region of the reticle. Generally, the method willalso involve storing in memory an association of the first imagingalgorithm with the first region of the reticle. In addition, the variousimaging algorithms may be ranked according to ability to suppressscattered radiation from valid features on the reticle.

In some embodiments, the image data is generated in multiple passes. Insuch embodiments, the process may involve the following: (I) carryingout a first scan of the reticle under a first apparatus setting fordetermining intensity of radiation scattered from the reticle as afunction of location on the reticle; (ii) carrying out a second scan ofthe reticle under a second apparatus setting which are different fromthe first apparatus setting; and (iii) selecting an apparatus settingbased upon ability to suppress scattered radiation from valid featureson the reticle. Preferably, (iii) is performed for each of a pluralityof regions of the reticle. Thus, the system will associate a selectedapparatus setting with one or more regions of the reticle, such thatduring the subsequent inspections of the reticle data from the selectedapparatus setting may be used to image the one or more regions.

These and other advantages of the present invention will be described inmore detail below in the detailed description of the invention and inconjunction with the following figures.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1A shows an idealized representation of an image of a reticle thatmay be used to identify defects according to the present invention.

FIG. 1B shows a top view of some significant components of a darkfielddetector that may be employed to scan and generate an image of a portionof a reticle.

FIG. 2A shows a flowchart, according to one embodiment of the presentinvention, ,of a process of determining whether a defect has appeared inthe reticle.

FIG. 2B shows a flowchart, according to one embodiment of the presentinvention, of a process for compacting a baseline image of a reticle.

FIG. 2C shows a flowchart, according to one embodiment of the presentinvention, detailing a process of comparing a current image to abaseline image of a reticle.

FIG. 3 shows a flowchart of a process, according to one embodiment ofthe present invention, of automatically determining which algorithms arebest suited for generating an image of a particular region of a reticle.

FIG. 4 shows a top view of a reticle inspection station and reticlestocker station where the process of FIG. 2A may be implemented in apreferred embodiment of the present invention.

DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

The present invention provides a process of identifying defects in areticle that arise over time—typically while the reticle is inoperation—by comparing an image of the reticle with a baseline image ofthe reticle when it was qualified. In the following description,numerous specific details are set forth in order to fully illustrate apreferred embodiment of the present invention. It will be apparent,however, that the present invention may be practiced without limitationto some specific details presented herein.

FIG. 2 shows a flowchart of a process 100 for identifying reticledefects that arise during the life of a reticle. The process is dividedinto two phases: a baseline image generating phase 116 and a comparisonphase 118. Baseline image generation phase 116 may begin at a step 102that includes qualifying a reticle, a baseline image of which willsubsequently be generated. A reticle is “qualified” when it is known tobe of acceptable quality. This means that the reticle is deemedsufficiently free of problematic defects that it can be used withconfidence during photolithography. As a result, a qualified reticleshould not be responsible for a relatively low yield or other problemwith the electronic devices fabricated by using of the reticle.

After the reticle is qualified, a baseline image of the qualifiedreticle is generated at a step 104. Step 104 may be carried out using aninspection apparatus such as the scattered light detecting assemblyshown in FIG. 1B. In this step, the intensity of the energy scatteredfrom an illuminated reticle surface is measured and recorded,pixel-by-pixel, as described above in the discussion pertaining to FIG.1B. In one embodiment, this may be carried out by scanning the reticlesurface in a single pass, during which the settings of the illuminatingsource and detectors are fixed. In another embodiment, this may becarried out by scanning the reticle in multiple passes, with the machinesettings varying from one scan to another. By way of example, one scanmay have different oblique angles of first detector 64 and seconddetector 68 with respect to the incident axis 70 than in another scan.As will be explained later, different settings of the illuminationsource and detectors may facilitate distinguishing between a real defectand false defect in different regions of a reticle.

Generally, step 104 is carried out contemporaneously with the step ofqualifying the reticle. The term “contemporaneously,” as used inconnection with the description of this invention means that thebaseline image of the reticle is generated relatively soon after thereticle is qualified or after any period of time, e.g., a few minutes toa few days or more, when it is reasonable to believe that no new defectshave been introduced into the qualified reticle.

Next, in a step 106, the baseline image of the reticle is divided intovarious segments, each of which corresponds to a separate region on thereticle. The term “region,” as used herein, refers to a relatively smallsection of the reticle. By way of example, very dark area 12, darkpatterned area 14 and bright patterned area 16 of FIG. 1A each may bedivided into several regions. At the extreme, each region or segmentcorresponds to a separate pixel. Typically, the regions will comprise atleast a few pixels. To facilitate processing of image data, each regionwithin an area of a reticle is assigned an address and an intensityvalue (for the scattered radiation).

Next, in a step 108, the baseline image of the reticle generated in step104 is optionally compacted by reducing the quantity of image data forthose regions of the reticle that do not include a real defect or afalse defect (i.e., those regions without any features or defects thatscatter radiation to a level exceeding a threshold as measured by thedetector(s)). By way of example, much of the scattering data for thevery dark area 12 (which falls below the threshold for indicating adefect) may be deleted in this step. All that would remain are datadefining the coordinates of the boundaries of area 12.

Baseline generation phase 116 concludes with the system storing thebaseline image in either a compacted or uncompacted form. In the aboveexample, the stored baseline image includes detailed intensity data fordark pattern area 14 and bright pattern area 16 but very little, if any,intensity data for area 12.

By using compaction to reduce the data quantity in the baseline image,the memory storage space required to store the baseline image issignificantly reduced. Depending upon the image, compaction may reducethe stored data from on the order of gigabytes to on the order ofmegabytes, for example. Further, a compacted baseline image speeds upthe comparison step, which is described hereinafter.

The next phase of the process, comparison phase 118, takes place sometime after baseline generation phase 116. Generally, it will take placeafter there is reason to believe that the reticle could have becomedefective. For example, a comparison may be appropriate after thereticle has been used for a certain number of photolithographyoperations or has been in existence a certain length of time.Alternatively, a comparison may take place when the reticle has beensubjected to a potentially damaging event (e.g., mishandling). In anyevent, its purpose is to determine whether any new defects have arisenin the time since the reticle was qualified (deemed acceptable).

Comparison phase 118 begins with the system generating a new image ofthe reticle at a step 110. This new image may be generated by scanningthe reticle surface with a light beam and measuring the intensity of thescattered light as a function of position. This step may be performed inthe manner described with reference to step 104. While not critical tothe practice of this invention, it will generally be desirable to employthe same scattered light detecting assembly and apparatus settings asemployed to generate the baseline image. This will facilitate comparisonof the two images. In this step, the new image of the reticle may bestored in memory for subsequent comparison.

In a step 112, the baseline image generated in step 104 is compared withthe new image of the same reticle in step 110. The purpose of this stepis to identify any new defects indicating that the reticle should beretired. Next, in a step 114, the location of any real defect(s) foundduring comparison step 112 is stored in memory. This may simply involvemarking the address of the defect location as containing a real defect.The stored information may be evaluated by other software to determinewhether the new defect's type or location is sufficiently problematicthat the reticle should be retired or repaired. If the softwareconcludes that the reticle need not be replaced, then the new image maybe preserved for comparison with subsequently taken images. In suchcomparison, the new defect will not cause alarm. After step 114 iscompleted the comparison process ends.

QUALIFICATION

As mentioned above, the baseline image is taken while the reticle isbelieved to be acceptable. Typically the reticle will be known to beacceptable because it has been qualified. Thus, in process 100, thereticle is qualified at step 102. Qualification may be accomplished in anumber of different ways known to those of skill in the art. In onecase, the reticle undergoes a rigorous optical examination to identifyany defects, a priori. If the number and/or type of defects indicates aproblem, the reticle is rejected. By way of example, if more than about10 potential defects are identified, the reticle is rejected.

In one specific embodiment, the reticle is qualified with the KLASTARlight inspection system available from KLA-Tencor Corporation of SanJose, Calif. This and similar inspection systems analyze a reticlepixel-by-pixel by scanning the reticle with an illumination source andmonitoring the transmitted and reflected light. By accounting for thereflectivity and transmittance of glass and chrome or other materialemployed in the reticle, the system constructs a very accurate anddetailed image of the reticle from scan data. While such opticaltechniques unambiguously qualify a reticle, they are slow and expensive.Therefore, it is impractical to use them to periodically evaluate aworking reticle.

A reticle may also be qualified by an electronic test. In such cases, adie fabricated with the reticle under consideration is subjected to arigorous electrical test or battery of tests to confirm that it isoperating according to specification. If the die passes the test(s), itcan be assumed that the reticle (as well as every other piece ofapparatus in the fabrication process) is acceptable.

BASELINE IMAGE GENERATION

As mentioned in the discussion of step 104, a baseline image isgenerated for the purpose of providing an image of the reticle while ina qualified state. Later, the system compares this baseline image to anew image of the reticle in order to identify any new defects. Thebaseline image is necessary because many valid features on the reticlescatter light nearly as strongly as—if not as strongly as—real defects.In order to clearly distinguish between scattering from valid structures(false defects) and scattering from real defects, the system needs tocompare the two images.

Briefly, the intensity of a scattered energy signal of a reticle feature(or defect) is highly dependent on the geometry and environment of thatfeature, e.g., the density of the lines at the reticle feature and theangle of these lines with respect to the incident axis and the obliqueangle of the scattered light detectors, etc. If the density of lines ofthe die feature is relatively high, i.e. the distance separating thelines is small, the intensity of scattered light signal can besignificant.

COMPACTION

FIG. 2B illustrates one approach to implementing step 108 of process 100(i.e., compacting a baseline image). Process 108 begins with aniterative loop step 302, in which “j” is an index denoting a particulardomain or region of the reticle (obtained during segmenting step 106)and “R” denotes the total number of regions present in the reticle.Iterative loop step 302 initially sets the value of j to 1. Thisspecifies the first region of the baseline image to be considered.Subsequently, step 302 increments the value of j successively until itexceeds the value of R.

After selecting the region having the current index, j, the systemdetermines whether the intensity of scattered radiation recorded forthat region is greater than a predefined threshold of intensity. Seestep 304. If so, the system stores in memory the intensity value of thescattered light and its location. See step 306. If, however, theintensity of scattered light recorded for the region under considerationis not greater than the predefined threshold, then the intensity datafor that region is not saved or is deleted. See step 308. However, thecoordinates of the region are noted so that the bounds of the “dark”region can ultimately be delineated.

After either step 306 or 308 is completed, process control returns toiterative loop step 302, where the value of index j is incremented by 1.Assuming that the value of j is still less than R, decision step 304 isreexecuted for the new region under consideration. After the intensitydata of all regions has been processed as described in steps 304, 306and 308 (i.e., j is greater than R), an output file containing savedregions of the baseline image is generated in a step 310. Process 100then proceeds to step. 108 as described above. Note that the output filealso delineates the boundaries of any dark regions for which reduced orno intensity data is maintained.

COMPARISON

The process of comparing the new and baseline images (step 112 ofprocess 100) may begin with a sequential examination of pixels or othersmall domains of the new image. For each pixel or domain, the systemdetermines whether the intensity of scattered radiation is greater thana predefined threshold of intensity (preferably the threshold set forstep 108). If the intensity does not exceed the threshold, then thesystem moves to the next pixel where the intensity of scattered light isconsidered. If, on the other hand, the intensity does exceed thethreshold, then the system determines whether a false defect (brightspot) is present in the corresponding pixel of the baseline image.Should a similarly bright spot be present in the baseline image, it isassumed that the radiation was scattered by a valid feature (falsedefect). Should no corresponding bright spot reside in the baselineimage, the system concludes that a real defect may be present and savesthe intensity and location information.

FIG. 2C shows one process flow for implementing step 112 of process 100.The step of comparing the baseline image to the new image of the reticlebegins at an iterative loop step 252, in which “k” is an index denotingthe particular region of the reticle under consideration and “T” denotesthe total number of regions present in the reticle. Often the value of Twill equal the value of R (FIG. 2B). Iterative loop step 252 initializesthe value of k to 1, compares the current value of k to T, and directsprocess control to a decision step 253 when k is less than or equal toT.

In decision step 253, the system determines whether the intensityreading of the region under consideration exceeds the threshold value.If not, no defect resides in the region, and process control returns tostep 252, where the value of k is incremented by 1. However, if theintensity reading of the region under consideration exceeds thethreshold, then process control is directed to a comparison step 254. Instep 254, the system determines whether the absolute value of thedifference in intensity of scattered light in the new image of a regionand the intensity of scattered light in the baseline image of the regionexceeds a predefined deviation value. If so, a real defect is indicatedand the system marks the region as containing a defect at a step 256.Thereafter process control returns to step 252 where the value of k isincremented by 1. If the system determines that the absolute value ofthe difference in intensity of scattered light in the new image of aregion and the intensity of scattered light in the baseline image of theregion does not exceed a predefined deviation value (i.e., step 254 isanswered in the negative), then it is established that there are no newreal defects present in the reticle.

After R number of regions of the reticle are examined as describedabove, an output file containing real defects and their location or theaddress of their region is generated in step 258. Process 100 thenproceeds to step 114 as described with reference to FIG. 2A.

It may be noted that in the event the region under consideration wascompacted in step 108, then the comparison performed in step 254 employsa null value of scattered light intensity. This means that any detectorreading above the threshold in such regions will be considered torepresent a real defect.

TRAINING ALGORITHMS

An image (baseline or new) may be generated from detector data by any ofa number of algorithms. The simplest algorithm presents each pixel of animage exactly as the intensity read by a detector for the correspondingpoint on the reticle. If there are two or more detectors, then theaverage of their readings may be employed. In more complex algorithms,the image value of any given pixel may be influenced by the detectorreadings a group of neighboring locations on the reticle. For example,some form of interpolation may be employed. Other algorithms may employfunctions to weight the contributions to the image that the variousdetectors make for any given pixel.

The goal of any of these algorithms is to discriminate between real andfalse defects. For a given detector setting and reticle pattern, somealgorithms will do a better job than others. Because reticle patternsvary in density, shape, and angle over the surface of the reticle, it isnot surprising that an algorithm that works best at one region of thereticle will not work best at some other region of the reticle. Thus, apreferred embodiment of the invention employs determines which of aplurality of imaging algorithms works best for any given region of thereticle image. The end result, is a mapping of imaging algorithms toregions of the reticle image. Then during reconstruction of the image,the imaging algorithm mapped to a given region is used to generate theimage of that region.

FIG. 3 shows a process 120 of automatically mapping imaging algorithmsto regions of the reticle. Preferably, this process is applied to thebaseline image. Then, when the new image is being generated, thealgorithms identified in process 120 are employed at the appropriateregions to generate the new image.

Process 120 begins at a step 121, which includes selecting a firstregion of the reticle. Next, in a step 122, “N” number of algorithms tobe tried are selected or identified. Representative algorithms includemathematical functions that consider the intensity of scattered energydetected by a single detector, the difference in the intensity detectedby two detectors, the optimum value for the predefined threshold ofintensity of scattered energy, the average intensity of the surroundingpixels or regions, the difference between the intensities of twoneighboring pixels or regions, the application of filter, etc.

The process of optimizing an algorithm for a specific region begins atan iterative loop step 124, in which “i” is an index denoting an initialalgorithm index and “N” denotes the total number of algorithms that mayapply to a region of the reticle. Iterative loop step 124 iterates froma value of i that starts at 1 and is terminated when i equals N.

In a step 132, an algorithm(i) is applied to the current region of thereticle. Next, in a step 134, the sensitivity of the algorithm withrespect to that region is determined and saved in memory. The term“sensitivity” as used in connection with the description of thisinvention refers to the ability of the algorithm to distinguish betweena real defect and a false defect. The iterative loop continues toconsider additional algorithms, determining and saving theirsensitivities, until N algorithms are applied to the region. Then, in astep 136, the various algorithms are ranked according to theirsensitivity. It is important to note that sensitivity to real defects(e.g., contaminants, etc.) is relatively fixed and well established.This process determines sensitivity to “false defects.”

Next, in step 138 it is determined whether the region underconsideration is the last region. If so, the process is concluded. Ifnot, the iterative loop described above proceeds to rank the algorithmsaccording to their sensitivity for another region of the reticle. Thisprocess continues until all the regions are evaluated. In the end, thealgorithms and their rank are saved in memory to facilitate future scansin effectively discerning between a real and false defect.

According to an alternative embodiment of process 120, index “i” as setforth in step 124 may refer to an initial machine setting index, insteadof an initial algorithm index as described above. “Machine settings” asthat term is used herein refers to the settings of the system thatgenerates the scattering data. Examples of machine setting parametersinclude the intensity and orientation of the illuminating source, theorientation of the detectors, the filtering of the detectors, theincident light polarization, etc. Each machine setting parameter can beadjusted to better discriminate between real and false defects.

In one simple case, a first scan of the reticle is conducted with adetector oriented at a first angle with respect to an incident axis andthe plane of the reticle. In a second scan, the detector is oriented ata second angle with respect to the incident axis and the reticle plane.Multiple such settings may be considered during the iterations set forthin process 120. For each region considered, the different machinesettings can be ranked according to their sensitivity.

With reference to FIG. 2A, this embodiment may affect the implementationof step 110. Specifically, if step 104 is carried out in multiple passes(each with a different machine setting), step 110 should be carried outwith the same group of passes. The results of one scan will be appliedto a first group of image regions, the results of a second scan will beapplied to a second group of image regions, etc. This will, of course,slow the imaging process, but in some cases will produce an overallbetter comparison of the baseline and new reticles.

FIG. 4 shows a reticle inspection station-reticle stocker station 200where process 100 of FIG. 2A would be implemented in a preferredembodiment of the present invention. An autoloader 208 for automaticallytransporting reticles includes a robot 212 having an arm 210 extendingtowards a inspection port of a reticle inspection station. Arm 210 mayrotate and can extend towards an external port 204 when in its statedenoted by reference number 210′. Similarly, when in its state denotedby reference number 210″, the robotic arm can also extend towards astorage port 206 of a reticle stocker station 216 that typicallyincludes several slots or tracks for storing reticles. The robotic armis designed to further extend and retrieve a reticle 214 from reticlestocker station 216.

A typical inspection process, according to one embodiment of the presentinvention, may begin after reticle 214 is qualified and placed onexternal port 204, with the intention of storing the reticle in reticlestocker station 216 until it is used in a subsequent conventionalphotolithography application, for example. Robotic arm in its position210′ transports the reticle from external port 204 and stores it in aloading port of reticle stocker station 216 by extending as shown inFIG. 4. When the reticle is needed for production, for example, roboticarm 210″ retrieves reticle 214 from the loading port and places it oninspection port 202, where comparison phase 118 of FIG. 2A detailedabove is carried out and it is determined whether new real defects haveappeared in the reticle. After the reticle inspection has concluded,reticle 214 is placed on external port 204 so that it may be carried toa fabrication facility for use.

Those skilled in the art will appreciate that the vendor who hasqualified the reticle may provide the end user of the reticle, e.g. afabrication facility, with the baseline image of the reticle and performthe steps of baseline generation phase 116 detailed in FIG. 2A.

Suitable computer systems for use in implementing and controlling themethods in the present invention (e.g., controlling the settings of thevarious scanning apparatus components, storing baseline image of thereticle, segmenting the baseline image, compacting the baseline image,storing new image of the reticle, comparing the new image with thebaseline image, storing the location of real and false defects, etc.)may be obtained from various vendors. In one preferred embodiment, anappropriately programmed HP735 workstation (Hewlett Packard, Palo Alto,Calif.) or Sun ULTRASPARC or Sun SPARC (Sun Microsystems, Sunnyvale,Calif.) may be employed. In any case, the computer system preferably hasone or more processors coupled to input/output ports, and one or morememories via appropriate buses or other communication mechanisms.

Preferably, an illumination system such as illustrated in FIG. 1B isintegrated with a computer system which implements many of the methodsteps of this invention. Such composite system preferably includes atleast (a) a baseline image (preferably compacted) stored in a memory,(b) an imaging system arranged to generate a current image of thereticle, and (c) a processing unit configured to compare the baselineand current images and thereby identify any new defects that may havearisen in the time between when the baseline image was created and whenthe current image is generated. At a minimum, the imaging system willusually include (i) a source of illumination oriented to direct lightonto a specified location of the reticle; and (ii) one or more detectorsoriented to detect light from the source which has been scattered by thereticle. The imaging system may also include a scanning means.

It should be understood that the present invention also relates tomachine readable media on which are stored instructions for implementingthe invention. Such instructions facilitate the comparison of thebaseline image with the new image of the reticle and the provision ofoptimizing algorithms, settings of the illuminating source or detectorsbased on a certain predetermined criteria. Such media includes, by wayof example, magnetic disks, magnetic tape, optically readable media suchas CD ROMs, semiconductor memory such as PCMCIA cards, etc. In eachcase, the medium may take the form of a portable item such as a smalldisk, diskette, cassette, etc., or it may take the form of a relativelylarger or immobile item such as a hard disk drive or RAM provided in acomputer.

The present invention described above represents a marked improvementover the current approaches of identifying the location of real defectsin a reticle. By way of example, the present invention can effectivelyidentify the location of real defects in a reticle containing thepattern for only a single die. As another example, the present inventionidentifies the location of real defects with significant accuracy andspeed. As yet another example, the present invention can effectivelyfind small real defects in the presence of large signals that aregenerated by die features that are not real defects.

Although the foregoing invention has been described in some detail forpurposes of clarity of understanding, it will be apparent that certainchanges and modifications may be practiced within the scope of theappended claims. For example, while the specification has describedmethods of identifying defects as applicable to reticle evaluation,there is no reason why, in principle, these methods of identifyingdefects cannot be applied to other objects that may become defectiveover time. For example, the invention could be applied to identifydefects in other optical elements used in photolithography. Therefore,the present embodiments are to be considered as illustrative and notrestrictive, and the invention is not to be limited to the details givenherein, but may be modified within the scope of the appended claims.

What is claimed is:
 1. A method for identifying a defect in a reticlecontaining features that scatter light, which features together define apattern to be transferred a substrate surface, the method comprising:providing a baseline image of said reticle which baseline image wascreated while the reticle was qualified as being of acceptable quality;generating a current image of the reticle; and comparing the baselineand current images wherein the differences between these images identifydefects that may have arisen in the time between when the baseline imagewas created and when the current image is generated.
 2. The method ofclaim 1, wherein said features that scatter light include features thatmodulate light transmission.
 3. The method of claim 2, wherein saidfeatures that scatter light include features that are opaque ortransparent to light.
 4. The method of claim 1, wherein the currentimage is generated by scanning said reticle to develop an image of saidreticle.
 5. The process of claim 4, wherein each pixel of the currentimage is generated by a method comprising: illuminating a region of saidreticle by an incident beam generated by an illuminating source;detecting a scattered energy distribution from said region of saidreticle by a detector; and recording said scattered energy distributionfrom said region of said reticle.
 6. The process of claim 1, whereincomparing the baseline and current images includes: determining whetherintensity of scattered radiation at a first location of the currentimage is greater than a defined threshold; if the scattered radiationfrom the first location is greater than the defined threshold,determining whether an absolute value of a difference between theintensity of scattered light at the first location and the intensity ofscattered light in a corresponding region of the baseline image of theregion exceeds a predefined deviation value; and if the absolute valueof the difference between the intensity of scattered light at the firstlocation and the intensity of scattered light in the correspondingregion of the baseline image of the region exceeds a predefineddeviation value, flagging a defect at the first location.
 7. A method ofinspecting an object, comprising: (a) providing an object to beinspected; (b) storing a baseline image of the object at a time when theobject is known to be of acceptable quality; (c) inspecting the objectat a time when the object is not known to be of acceptable quality; (d)comparing data derived from the inspection with data derived from thestored baseline image; and (e) identifying defects on the object basedon the comparison.
 8. The method of claim 7, wherein the object is areticle.
 9. The method of claim 7, wherein the stored baseline imagecontains data correlating the intensity of radiation scattered from theobject with locations of the object.
 10. The method of claim 9, whereinstoring the baseline image includes compacting the baseline image toreduce the quantity of stored data for portions of the image where theintensity of the scattered radiation does not exceed a definedthreshold.
 11. The method of claim 10, wherein compacting includes thefollowing: segmenting the baseline image into regions of the object; andremoving data from the baseline image for those regions of said objectwhere the intensity of the scattered radiation does not exceed thedefined threshold.
 12. The method of claim 7, wherein the object isknown to be of acceptable quality by subjecting it to an opticalqualification technique.
 13. The method of claim 8, wherein the objectis known to be of acceptable quality by subjecting it to a methodcomprising: electronically testing at least one die fabricated on alsubstrate by process employing and reticle; and determining whether saidat least one die passes the testing, in which case the reticle isqualified.
 14. The method of claim 7, wherein inspection is performed bygenerating a darkfield image of the object.
 15. The method of claim 8,wherein inspection of the object includes measuring and recordingscattered light from the object as a function of position on thereticle.
 16. The method of claim 7, wherein defects are identified atlocations wherein the inspection data and the baseline image datadeviate from one another.
 17. A method of providing a baseline image ofa reticle for use in subsequent inspections of the reticle, comprising:(a) providing the reticle to be inspected; (b) generating dataspecifying intensity of radiation scattered from the reticle as afunction of location on the reticle; (c) defining a first portion of thedata which was derived from a first region on the reticle; (d) applyinga plurality of imaging algorithms to the first portion of the data; (e)selecting a first imaging algorithm from among the plurality of imagingalgorithms based upon ability to suppress scattered radiation from validfeatures on the first region of the reticle; and (f) associating thefirst imaging algorithm with the first portion of data in the baselineimage, such that during the subsequent inspections of the reticle thefirst imaging algorithm is applied to the first portion of the data toprovide an image of the first region of the reticle.
 18. The method ofclaim 17, further comprising ranking the plurality of imaging algorithmsaccording to ability to suppress scattered radiation from valid featureson the reticle.
 19. The method of claim 17, further comprising storingin memory an association of the first imaging algorithm with the firstregion of the reticle.
 20. The method of claim 17, wherein generatingdata specifying intensity of radiation comprises: (i) carrying out afirst scan of the reticle under a first apparatus setting fordetermining intensity of radiation scattered from the reticle as afunction of location on the reticle; (ii) carrying out a second scan ofthe reticle under a second apparatus setting which are different fromthe first apparatus setting; (iii) selecting an apparatus setting basedupon ability to suppress scattered radiation from valid features on thereticle.
 21. The method of claim 20, wherein (iii) is performed for eachof a plurality of regions of the reticle.
 22. The method of claim 21,further comprising associating a selected apparatus setting with one ormore regions of the reticle, such that during the subsequent inspectionsof the reticle data from the selected apparatus setting may be used toimage the one or more regions.
 23. A system for identifying a defect ina reticle containing transparent regions and opaque regions defining apattern to be transferred a substrate surface, the system comprising: abaseline image stored in a memory, the baseline image being an image ofthe reticle taken while the reticle was known to be of acceptablequality; an imaging system arranged to generate a current image of thereticle, which current image corresponds to the baseline image; and aprocessing unit configured to compare the baseline and current imagesand thereby identify any new defects that may have arisen in the timebetween when the baseline image was created and when the current imageis generated.
 24. The system of claim 23, wherein the baseline imagecontains data correlating the intensity of radiation scattered from theobject with locations of the object.
 25. The system of claim 23, whereinthe baseline image is compacted.
 26. The system of claim 23, wherein theimaging system includes: a source of illumination oriented to directlight onto a specified location of the reticle; and one or moredetectors oriented to detect light from the source which has beenscattered by the reticle.